Chris Law

Even the most skeptical voices are starting to acknowledge the value of LLM generated code. Not as a replacement for deep expertise, but as a practical tool for acceleration, exploration, and iteration. When someone as famously disciplined about code quality as Linus Torvalds publicly acknowledges that AI generated code can be useful, it signals a shift worth paying attention to. The takeaway is not that AI writes better software than humans, but that good engineers are learning where and how these tools create leverage. https://lnkd.in/eFbNFqYN

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In the San Francisco Bay Area, founders are relentless about growing and scaling their companies. They spot opportunity, scale through uncertainty, and create companies that redefine industries. Recently, we gathered a group of founders and tech leaders to discuss the intersection of company growth and long-term personal success. Eric S. Yuan, Founder and CEO of Zoom Communications, shared the inspiring story behind his company’s growth and eventual IPO. Eric reiterated that the founders who create the most impact don’t just plan for an exit – they prepare for what comes after. Too often, personal wealth planning lags company growth, and that gap can become costly at the most pivotal moments. The rest of the evening was focused on closing that gap. Our colleagues in Goldman Sachs Investment Banking, Pawan Tewari and Nick Giovanni, shared a candid outlook for M&A and IPOs in this environment, along with important steps founders should take to prepare for a strategic exit. We ended with a conversation around the key considerations for maximizing founders’ personal outcomes. Pre-transaction planning isn’t defensive - it’s opportunistic. Your company’s exit strategy and your family’s long-term planning work should not be done in isolation. When investment banking and private wealth work in sync, founders can cohesively optimize outcomes on all sides of the equation. To learn more about the practical “do’s and don'ts” for founders, we are happy to share our ‘Goldman guide’ for navigating wealth planning, business exists, and IPOs: https://lnkd.in/ewhEGjV3. Thank you, Eric, and to all the founders who joined us at The Battery in SF. On behalf of Goldman Sachs Private Wealth Management and Investment Banking, we look forward to the next conversation.

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My thoughts on the Great Waymo Outage and what it means for human acceptance of AI/technology. Two quick hits. Waymo needs a more graceful failure mode. Just pulling to the roadside might work in a normal power outage but not in, say, a wildfire or in the aftermath of a quake when people need to get out of harm's way. People also need to reconcile that the big, scary outages are easy to fixate on but mask the overall higher levels of safety and reliability we will be seeing from mature (note the word) AI systems. https://lnkd.in/gwnUA_hJ

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LLMs aren’t good enough yet for the general public to use it for shopping… but they’re getting dangerously close. When AI cracks commerce, traffic behavior will change faster than most businesses are ready for.👇

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U.S. energy demand is surging — don’t get left behind. New gas projects and large industrial loads are reshaping power markets at breakneck speed. In this high-stakes landscape, timely and accurate data is essential. Halcyon’s Data Products, powered by a regularly updated authoritative data catalog of 4.5+ million documents from all 50 public utility commissions, ensure you always have the latest energy market intelligence. Download this guide to see how AI can help power sector stakeholders find new growth opportunities first.

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Thrilled to announce that Together Fund is investing in Sentra, alongside a16z speedrun! You track results in Jira. Decisions in Notion. Conversations in Slack. But the reasoning, the debates, trade-offs, and context behind why you chose A over B, disappears into what we call "Dark Matter." A decision made in March looks insane by July because no one remembers the constraints that made it smart. I lived this firsthand at Twitter scaling from 800 to 8,000 employees, and at Google while launching AI Overviews to billions at planet scale. The problem isn't process. Process is compensation for something deeper: organizational amnesia. An organization’s "Systems of Record" doesn’t solve this, they encode it. They store what happened, never why. That's why we are investing in Sentra. Sentra is the always-on collective memory that eliminates organizational amnesia by maintaining accurate context for all members and agents, functioning as an operational nervous system. It connects to every channel where work happens, meetings, Slack, email, code commits, docs, calendars, and treats them not as artifacts to search, but as living signals to synthesize. The fleeting and the permanent, unified into a memory that understands. The founding team is built for this: - Jae Gwan Park (CEO): Product-first founder, memory systems research at UofT and MIT - Ashwin Gopinath (CSO): Former MIT professor, created "Reflexion" (NeurIPS 2023), agents that learn from mistakes, 2x founder - Andrey Starenky (CTO): Early Vapi engineer, ex-IBM, built to process enterprise-scale data firehose Together is an operator-led fund. We invest in problems we've lived. This is one of them. Many congrats Jae, Ashwin and Andrey, we are so excited to partner with you! Read the full thesis: https://lnkd.in/gixj9cE4 Book a demo: https://www.sentra.app/ #OrganizationalMemory #AI #Sentra #TogetherFund #a16z #ContextGraphs

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We chose a good subject for our march Autotech Council meeting, and after this year's CES, it seems even more obvious. Our meeting on the AI Defined Vehicle will show how it's a natural next step after the Software Defined Vehicle phase that we've been in Tesla launched the Model S in 2012. Now, most carmakers have SDVs. It's time to layer on the AI in user-facing roles, and in invisible functions managing the vehicle.

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Seattle VC panels are not exactly known for being spicy, which is why my AMA with Brooke and Rolanda at AI House last night was so refreshing. We got into the questions founders are too embarrassed to ask out loud. How do VCs actually decide behind closed doors? What counts as traction when you have zero revenue? Is enterprise SaaS dead? Do Seattle founders actually have a shot against the Bay Area? A few takeaways that stood out: ✅ Associates can't get to yes without a partner sponsor — but partners often can't reach deals without associate diligence. Arm them with the facts to fight for you internally. ✅ Expect 50-70 investor conversations before a term sheet. Send your deck a day early but assume nobody read it 😎 ✅ Enterprise SaaS isn't dead, but it's shifting from seat-based to usage and outcome-based pricing. Large orgs still need governed software. ✅ Traction isn't just revenue. How excited are your customers? Would they advocate for you? Paying pilots with automatic, KPI-specific conversion > free trials, every time. ✅ Learning slope > starting background. The strongest founders they've backed adapted fast — not started perfect. Brooke and Rolanda WILL take a second meeting even if you whiff the first one! ✅ Seattle has fantastic enterprise buyers and founders with sales relationships into them. But the equity-vs-cash culture gap is real, and hiring against big tech is still hard. What made it different was how candid Brooke and Rolanda were about what actually happens after your pitch ends, aka the internal deal dynamics most founders never see. Shoutout to the room full of 100+ early-stage founders who went against the Seattle grain and asked hard questions live to the VCs. That energy is what makes AI House work. Huge thanks to Brooke B. (FUSE) and Rolanda Fu (Madrona) for keeping it real! More AMAs like this coming. Tag a founder who we should invite for the next one! #AIHouse (photo credit to Jonathan G. Blanco 🛠)

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Ontologies remain one of the most effective ways to ground AI memory, keeping extracted knowledge anchored to existing structures and adaptable through feedback. As memory systems evolve, their role remains essential, and a core focus at Cognee.

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The hottest role in AI startups right now isn’t Forward Deployed Engineers. It isn't GTM Engineers. It’s Deployment Strategists. Decagon calls it an “Agent Product Manager.” Harvey calls it a “Solutions Architect.” Palantir Technologies has had versions of this role for years. And the salaries are climbing fast: - Decagon: $200k–$285k - Palantir Technologies: $120k–$200k - Figma: $150k–$260k - Ramp: $100k–$180k - Harvey: $190k–$260k So who are these people? They are usually pseudo-technical -- CS or engineering majors, or folks with technical work experience. Many come from 2 years in consulting, IB, or PE, then jump into startups to get their hands dirty. They are young, hungry, polished, and comfortable being in front of customers. What do they actually do? They make sure enterprise AI deployments succeed. A $100k+ deal does not survive on a nice pitch or a self-serve onboarding flow. It survives if the customer sees value in the pilot. That means: - Embedding directly with the customer - Designing prompt logic for specific workflows - Working with engineering to align integrations and data flow - Helping exec teams define their AI roadmap - Running feedback loops into product and GTM Why does this role matter so much? Because enterprise AI is messy. Integrations, data transfer, and adoption make or break a deal. Most buyers are using AI for the first time, and each has unique workflows. Deployment Strategists bridge that gap. They own the outcome. They are accountable for making pilots successful, which often means millions in revenue down the line. At Conversion, Sam Bochner has been leading this work for us. We are now thinking about scaling it into a full team. Because a few successful pilots can fund an entire department, and the cost of failed deployments is too high to ignore. Is this just a rebrand of customer success? Not really. Success is about answering tickets and renewals. Deployment Strategy is about going deep with a few enterprise accounts, extracting maximum value, and ensuring the pilot closes into a multi-year contract. Call it Agent PM, Solutions Architect, or Deployment Strategist. Whatever the title, this is becoming one of the most important roles in AI SaaS.

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